MinimumEigenOptimizationResult

class MinimumEigenOptimizationResult(x, fval, variables, status, samples=None, min_eigen_solver_result=None, raw_samples=None)

Bases: OptimizationResult

Minimum Eigen Optimizer Result.

Parameters:

• x (list[float] | np.ndarray | None) – the optimal value found by SamplingMinimumEigensolver or NumPyMinimumEigensolver.

• fval (float | None) – the optimal function value.

• variables (list[Variable]) – the list of variables of the optimization problem.

• status (OptimizationResultStatus) – the termination status of the optimization algorithm.

• min_eigen_solver_result (MinimumEigensolverResult | None) – the result obtained from the underlying algorithm.

• samples (list[SolutionSample] | None) – the x values, the objective function value of the original problem, the probability, and the status of sampling.

• raw_samples (list[SolutionSample] | None) – the x values of the QUBO, the objective function value of the QUBO, and the probability of sampling.

Attributes

fval

Returns the objective function value.

Returns:

The function value corresponding to the objective function value found in the optimization.

min_eigen_solver_result

Returns a result object obtained from the instance of SamplingMinimumEigensolver or NumPyMinimumEigensolver.

raw_results

Return the original results object from the optimization algorithm.

Currently a dump for any leftovers.

Returns:

Additional result information of the optimization algorithm.

raw_samples

Returns the list of raw solution samples of SamplingMinimumEigensolver or NumPyMinimumEigensolver.

Returns:

The list of raw solution samples of SamplingMinimumEigensolver or NumPyMinimumEigensolver.

samples

Returns the list of solution samples

Returns:

The list of solution samples.

status

Returns the termination status of the optimization algorithm.

Returns:

The termination status of the algorithm.

variable_names

Returns the list of variable names of the optimization problem.

Returns:

The list of variable names of the optimization problem.

variables

Returns the list of variables of the optimization problem.

Returns:

The list of variables.

variables_dict

Returns the variable values as a dictionary of the variable name and corresponding value.

Returns:

The variable values as a dictionary of the variable name and corresponding value.

x

Returns the variable values found in the optimization or None in case of FAILURE.

Returns:

The variable values found in the optimization.

Methods

get_correlations()

Get <Zi x Zj> correlation matrix from the samples.

Returns:

A correlation matrix.

Return type:

ndarray

prettyprint()

Returns a pretty printed string of this optimization result.

Returns:

A pretty printed string representing the result.

Return type:

str